Adaptive nonuniform polar quantization application to high quality speech compression

The logarithmic companding technique has shown to be extremely useful in speech quantization with rate of 8 bits/sample. However, for lower bit rates it is not the ideal solution for high quality speech coding. Because of that, in this paper we establish source coding scheme which enables better spectrum efficiency for input that has a large dynamic range. Since our wish is also to improve signal quality in comparison with quality defined with standards G.711 and G.712, we opt for adaptive technique application to the speech coding. Our research shows that proper design of forward gain-adaptive polar quantization can enable compression of about 1 bit/sample as well as significantly better quality than in case of using coder designed according to standard G.711. Furthermore, performances can be sustained over the whole speech dynamic range. Also, if the requisite speech quality is not supposed to be lower than G.712 standard quality, the achieved compression can be almost 1.5 bits/sample. Besides, we propose knew simple encoding rule which can additionally reduce bit rate for 0.1 bit/sample.     

Negative bias temperature instability in n-channel power VDMOSFETs

Negative gate bias is used in some applications for faster switching off the n-channel MOS devices. It is shown in this study that NBT stress-related instability in commercial n-channel power VDMOSFETs could be actually more serious than in corresponding p-channel devices. NBT stress is found to create equal V_T shifts in both device types, whereas the subsequent positive bias annealing results in more serious overall V_T instability in n-channel devices. The changes in the densities of stress-induced interface traps in two device types are equal as well, but significant amounts of NBT stress-induced border traps are only found in n-channel devices. All the results are discussed in terms of hydrogen reaction and diffusion model.     

Modeling of dibenzothiophene oxidative desulfurization using response surface methodology

The effect of reaction temperature, mixing speed and oxidant to catalyst volume ratio, including their interactions on the oxidative desulfurization of dibenzothiophene by using response surface methodology was studied. Hydrogen peroxide was used as oxidant and acetic acid as catalyst. The obtained model accurately predicts conversion of dibenzothiophene and the best conversion of 98.7% was observed at temperature 70°C, mixing speed of 1250 rpm and oxidant to catalyst volume ratio of 1:1. At high temperatures, a major limitation of the desulfurization process is the mass transfer and the high mixing speed is needed to achieve an efficient process.     

High Definition Digital Fabrication of Active Organic Devices by Molecular Jet Printing

We introduce a high resolution molecular jet (MoJet) printing technique for vacuum deposition of evaporated thin films and apply it to fabrication of 30 μm pixelated (800 ppi) molecular organic light emitting devices (OLEDs) based on aluminum tris(8‐hydroxyquinoline) (Alq₃) and fabrication of narrow channel (15 μm) organic field effect transistors (OFETs) with pentacene channel and silver contacts. Patterned printing of both organic and metal films is demonstrated, with the operating properties of MoJet‐printed OLEDs and OFETs shown to be comparable to the performance of devices fabricated by conventional evaporative deposition through a metal stencil. We show that the MoJet printing technique is reconfigurable for digital fabrication of arbitrary patterns with multiple material sets and high print accuracy (of better than 5 μm), and scalable to fabrication on large area substrates. Analogous to the concept of “drop‐on‐demand” in Inkjet printing technology, MoJet printing is a “flux‐on‐demand” process and we show it capable of fabricating multi‐layer stacked film structures, as needed for engineered organic devices.     

Algorithm for tissue ischemia estimation based on electrical impedance spectroscopy

The purpose of this paper is to present an algorithm developed for real-time estimation of skeletal muscle ischemia, based on parameters extracted from in vivo obtained electrical impedance spectra. A custom impedance spectrometer was used to acquire data sets: complex impedance spectra measured at 27 frequencies in the range of 100 Hz-1 MHz, and tissue pH. Twenty-nine in vivo animal studies on rabbit anterior tibialis muscle were performed to gather data on the behavior of tissue impedance during ischemia. An artificial neural network (ANN) was used to quantitatively describe the relationship between the parameters of complex tissue impedance spectra and tissue ischemia via pH. The ANN was trained on 1249, and tested on 946 ischemic tissue impedance data sets. A correlation of 94.5% and a standard deviation of 0.15 pH units was achieved between the ANN estimated pH and measured tissue pH values.     

Electrosynthesized CuMgAl Layered Double Hydroxides as New Catalysts for the Electrochemical Reduction of CO2

In this study, new nanostructured CuMgAl Layered Double Hydroxide (LDH) based materials are synthesized on a 4 cm² sized carbonaceous gas diffusion membrane. By means of microscopic and spectroscopic techniques, the catalysts are thoroughly investigated, revealing the presence of several species within the same material. By a one-step, reproducible potentiodynamic deposition it is possible to obtain a composite with an intimate contact between a ternary CuMgAl LDH and Cu⁰/Cu₂O species. The catalyst compositions are investigated by varying: the molar ratio between the total amount of bivalent cations and Al³⁺, the amount of loading, and the molar ratios among the three cations in the electrolyte. Each electrocatalyst has been evaluated based on the catalytic performances toward the electrochemical CO₂ reduction to CH₃COOH at −0.4 V versus reversible hydrogen electrode  in liquid phase. The optimized catalyst, that is, CuMgAl 2:1:1 LDH exhibits a productivity of 2.0 mmol_CH3COOH g_cat⁻¹ h⁻¹. This result shows the beneficial effects of combining a material like the LDHs, alkaline in nature, and thus with a great affinity to CO₂, with Cu⁰/Cu⁺ species, which couples the increase of carbon sources availability at the electrode with a redox mediator capable to convert CO₂ into a C₂ product.     

Sparsity-driven reconstruction for FDOT with anatomical priors

In this paper we propose a method based on (2, 1)-mixed-norm penalization for incorporating a structural prior in FDOT image reconstruction. The effect of (2, 1)-mixed-norm penalization is twofold: first, a sparsifying effect which isolates few anatomical regions where the fluorescent probe has accumulated, and second, a regularization effect inside the selected anatomical regions. After formulating the reconstruction in a variational framework, we analyze the resulting optimization problem and derive a practical numerical method tailored to (2, 1)-mixed-norm regularization. The proposed method includes as particular cases other sparsity promoting regularization methods such as l(1)-norm penalization and total variation penalization. Results on synthetic and experimental data are presented.     

An Example of Human-Centric Sensor Network: Be Responsible Platform

The paper addresses the Be Responsible platform, a representative example of human-centric sensing network which, relying on the Info-Communication and Internet of Things concepts, aims to improve the communication between citizens, on one side, and government authorities, on the other side, with the purpose of resolving various problems encountered in a modern society. A widespread network of human-centric smartphone devices and PCs has been used as a valuable source of data collected and processed in order to trigger adequate actions upon problem resolving. In this way, humans acting as sensor operators and data sources become a powerful factor in improving their society. The Be Responsible platform enables the people to report the irregularities in various aspects of their social life (grey economy, misuse of government vehicles, ecology, traffic), and hence to take active part in resolving them. It also promotes positive and responsible social and institutional behavior, which has to be nurtured in any society seeking progress. The number of submitted reports as well as the money collected from the fine revenues and subsequently invested in projects of social good, undoubtedly prove that what could not be achieved through years of traditional government-led policy approach, was achieved in months of citizen engagement.